Source code for spherical_geometry.polygon

# -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
The `spherical_geometry.polygon` module defines the `SphericalPolygon` class for
managing polygons on the unit sphere.
"""

# STDLIB
from copy import deepcopy

# THIRD-PARTY
import numpy as np

# LOCAL
from spherical_geometry import great_circle_arc, vector

__all__ = ['SingleSphericalPolygon', 'SphericalPolygon',
           'MalformedPolygonError']


[docs] class MalformedPolygonError(Exception): pass
[docs] class SingleSphericalPolygon(object): r""" Polygons are represented by both a set of points (in Cartesian (*x*, *y*, *z*) normalized on the unit sphere), and an inside point. The inside point is necessary, because both the inside and outside of the polygon are finite areas on the great sphere, and therefore we need a way of specifying which is which. """ def __init__(self, points, inside=None): r""" Parameters ---------- points : An Nx3 array of (*x*, *y*, *z*) triples in vector space These points define the boundary of the polygon. It may contain zero points, in which it defines the null polygon. It may not contain one, two or three points. Four points are needed to define a triangle, since the polygon must be closed. inside : An (*x*, *y*, *z*) triple, optional This point must be inside the polygon. If not provided, an interior point will be calculated """ if len(points) == 0: # handle special case of initializing with an empty list of # vertices (ticket #1079). self._inside = np.zeros(3) self._points = np.asanyarray(points) return if not np.array_equal(points[0], points[-1]): points = list(points[:]) points.append(points[0]) if len(points) < 3: raise ValueError("Polygon made of too few points") self._points = points = np.asanyarray(points) new_inside = self._find_new_inside() if inside is None: self._inside = np.asanyarray(new_inside) if not self.is_clockwise(): self._points = points[::-1] else: self._inside = np.asanyarray(inside) if self.contains_point(new_inside) != self.is_clockwise(): self._points = points[::-1] def __copy__(self): return deepcopy(self) copy = __copy__ def __len__(self): return 1 def __repr__(self): return '%s(%r, %r)' % (self.__class__.__name__, self.points, self.inside) def __iter__(self): """ Iterate over all base polygons that make up this multi-polygon set. """ yield self # Alias for backwards compatibility iter_polygons_flat = __iter__ @property def points(self): """ The points defining the polygon. It is an Nx3 array of (*x*, *y*, *z*) vectors. The polygon will be explicitly closed, i.e., the first and last points are the same. """ return self._points @property def inside(self): """ Get the inside point of the polygon. """ return self._inside
[docs] def is_clockwise(self): """ Return True if the points in this polygon are in clockwise order. The normal vector to the two arcs containing a vertes points outward from the sphere if the angle is clockwise and inward if the angle is counter-clockwise. The sign of the inner product of the normal vector with the vertex tells you this. The polygon is ordered clockwise if the vertices are predominantly clockwise and counter-clockwise if the reverse. """ points = np.vstack((self._points, self._points[1])) A = points[:-2] B = points[1:-1] C = points[2:] orient = great_circle_arc.triple_product(A-B, C-B, B) return np.sum(orient) > 0.0
[docs] def to_lonlat(self): """ Convert `SingleSphericalPolygon` footprint to longitude and latitutde. Returns ------- lon, lat : list of float List of *lon* and *lat* in degrees corresponding to `points`. """ if len(self.points) == 0: return np.array([]) return vector.vector_to_lonlat(self.points[:,0], self.points[:,1], self.points[:,2], degrees=True)
# Alias for to_lonlat to_radec = to_lonlat
[docs] @classmethod def from_lonlat(cls, lon, lat, center=None, degrees=True): r""" Create a new `SingleSphericalPolygon` from a list of (*longitude*, *latitude*) points. Parameters ---------- lon, lat : 1-D arrays of the same length The vertices of the polygon in longitude and latitude. center : (*lon*, *lat*) pair, optional A point inside of the polygon to define its inside. degrees : bool, optional If `True`, (default) *lon* and *lat* are in decimal degrees, otherwise in radians. Returns ------- polygon : `SingleSphericalPolygon` object """ # Convert to Cartesian x, y, z = vector.lonlat_to_vector(lon, lat, degrees=degrees) points = np.dstack((x, y, z))[0] if center is not None: center = vector.lonlat_to_vector(*center, degrees=degrees) return cls(points, center)
# from_radec is an alias for from_lon_lat from_radec = from_lonlat
[docs] @classmethod def from_cone(cls, lon, lat, radius, degrees=True, steps=16): r""" Create a new `SingleSphericalPolygon` from a cone (otherwise known as a "small circle") defined using (*lon*, *lat*, *radius*). The cone is not represented as an ideal circle on the sphere, but as a series of great circle arcs. The resolution of this conversion can be controlled using the *steps* parameter. Parameters ---------- lon, lat : float scalars This defines the center of the cone radius : float scalar The radius of the cone degrees : bool, optional If `True`, (default) *lon*, *lat* and *radius* are in decimal degrees, otherwise in radians. steps : int, optional The number of steps to use when converting the small circle to a polygon. Returns ------- polygon : `SingleSphericalPolygon` object """ u, v, w = vector.lonlat_to_vector(lon, lat, degrees=degrees) if degrees: radius = np.deg2rad(radius) # Get an arbitrary perpendicular vector. This be be obtained # by crossing (u, v, w) with any unit vector that is not itself. which_min = np.argmin([u*u, v*v, w*w]) if which_min == 0: perp = np.cross([u, v, w], [1., 0., 0.]) elif which_min == 1: perp = np.cross([u, v, w], [0., 1., 0.]) else: perp = np.cross([u, v, w], [0., 0., 1.]) perp = vector.normalize_vector(perp) # Rotate by radius around the perpendicular vector to get the # "pen" x, y, z = vector.rotate_around( u, v, w, perp[0], perp[1], perp[2], radius, degrees=False) # Then rotate the pen around the center point all 360 degrees C = np.linspace(0, np.pi * 2.0, steps) # Ensure that the first and last elements are exactly the # same. 2π should equal 0, but with rounding error that isn't # always the case. C[-1] = 0 C = C[::-1] X, Y, Z = vector.rotate_around(x, y, z, u, v, w, C, degrees=False) return cls(np.dstack((X, Y, Z))[0], (u, v, w))
[docs] @classmethod def from_wcs(cls, fitspath, steps=1, crval=None): r""" Create a new `SingleSphericalPolygon` from the footprint of a FITS WCS specification. This method requires having `astropy <http://astropy.org>`__ installed. Parameters ---------- fitspath : path to a FITS file, `astropy.io.fits.Header`, or `astropy.wcs.WCS` Refers to a FITS header containing a WCS specification. steps : int, optional The number of steps along each edge to convert into polygon edges. Returns ------- polygon : `SingleSphericalPolygon` object """ from astropy import wcs as pywcs from astropy.io import fits if isinstance(fitspath, fits.Header): header = fitspath wcs = pywcs.WCS(header) elif isinstance(fitspath, pywcs.WCS): wcs = fitspath else: wcs = pywcs.WCS(fitspath) if crval is not None: wcs.wcs.crval = crval try: xa, ya = wcs.pixel_shape except AttributeError: xa, ya = (wcs._naxis1, wcs._naxis2) length = steps * 4 + 1 X = np.empty(length) Y = np.empty(length) # Now define each of the 4 edges of the quadrilateral X[0 :steps ] = np.linspace(1, xa, steps, False) Y[0 :steps ] = 1 X[steps :steps*2] = xa Y[steps :steps*2] = np.linspace(1, ya, steps, False) X[steps*2:steps*3] = np.linspace(xa, 1, steps, False) Y[steps*2:steps*3] = ya X[steps*3:steps*4] = 1 Y[steps*3:steps*4] = np.linspace(ya, 1, steps, False) X[-1] = 1 Y[-1] = 1 # Use wcslib to convert to (lon, lat) lon, lat = wcs.all_pix2world(X, Y, 1) # Convert to Cartesian x, y, z = vector.lonlat_to_vector(lon, lat) # Calculate an inside point lon, lat = wcs.all_pix2world(xa / 2.0, ya / 2.0, 1) xc, yc, zc = vector.lonlat_to_vector(lon, lat) return cls(np.dstack((x, y, z))[0], (xc, yc, zc))
[docs] @classmethod def convex_hull(cls, points): """ Create a new `SingleSphericalPolygon` from the convex hull of a list of points using the Graham Scan algorithm Parameters ---------- points: A list of points on the unit sphere Returns ------- polygon : `SingleSphericalPolygon` object """ points = np.asarray(points) # Find an extremal point, it must be on boundary j = np.argmin(np.arctan2(points[:,1], points[:,0])) extreme = points[j,:] points = np.vstack((points[0:j,:], points[j+1:,:])) # Sort points around extreme point by angle from true north north = [0., 0., 1.] ang = great_circle_arc.angle(north, extreme, points) pt = [points[i,:] for i in range(points.shape[0])] duo = list(zip(pt, ang)) duo = sorted(duo, key=lambda d: d[1]) points = np.asarray([d[0] for d in duo if np.isfinite(d[1])]) # Set the first point on the hull to the extreme point pbottom = extreme hull = [pbottom] # If a point is to the left of previous points on the # hull, add it to the hull. If to the right, the top # point is an inside point and is popped off the hull. # See any description of the Graham Scan algorithm # for a more detailed explanation. i = 0 inside = None while i < points.shape[0]: ptop = hull[-1] if ptop is pbottom: hull.append(points[i,:]) i += 1 else: pprevious = hull[-2] if great_circle_arc.triple_product(pprevious, ptop, points[i,:]) > 0.0: hull.append(points[i,:]) i += 1 else: inside = hull.pop() # Create a polygon from points on the hull return cls(hull, inside)
[docs] def invert_polygon(self): """ Compute the inverse (complement) of a single polygon """ poly = self.copy() poly._points = poly._points[::-1] poly._inside = np.asanyarray(self._find_new_outside()) return poly
def _contains_point(self, point, P, r): point = np.asanyarray(point) if np.array_equal(r, point): return True intersects = great_circle_arc.intersects(P[:-1], P[1:], r, point) crossings = np.sum(intersects) return (crossings % 2) == 0
[docs] def contains_point(self, point): r""" Determines if this `SingleSphericalPolygon` contains a given point. Parameters ---------- point : an (*x*, *y*, *z*) triple The point to test. Returns ------- contains : bool Returns `True` if the polygon contains the given *point*. """ return self._contains_point(point, self._points, self._inside)
[docs] def contains_lonlat(self, lon, lat, degrees=True): r""" Determines if this `SingleSphericalPolygon` contains a given longitude and latitude. Parameters ---------- lon, lat: Longitude and latitude. Must be scalars. degrees : bool, optional If `True`, (default) *lon* and *lat* are in decimal degrees, otherwise in radians. Returns ------- contains : bool Returns `True` if the polygon contains the given *point*. """ point = vector.lonlat_to_vector(lon, lat, degrees=degrees) return self._contains_point(point, self._points, self._inside)
# Alias for contains_lonlat contains_radec = contains_lonlat
[docs] def intersects_poly(self, other): r""" Determines if this `SingleSphericalPolygon` intersects another `SingleSphericalPolygon`. This method is much faster than actually computing the intersection region between two polygons. Parameters ---------- other : `SingleSphericalPolygon` Returns ------- intersects : bool Returns `True` if this polygon intersects the *other* polygon. Notes ----- The algorithm proceeds as follows: 1. Determine if any single point of one polygon is contained within the other. 2. Deal with the case where only the edges overlap as in:: : o---------o : o----+---------+----o : | | | | : o----+---------+----o : o---------o In this case, an edge from one polygon must cross an edge from the other polygon. """ if not isinstance(other, SingleSphericalPolygon): raise TypeError # The easy case is in which a point of one polygon is # contained in the other polygon. for point in other._points: if self.contains_point(point): return True for point in self._points: if other.contains_point(point): return True # The hard case is when only the edges overlap, as in: # # o---------o # o----+---------+----o # | | | | # o----+---------+----o # o---------o # for i in range(len(self._points) - 1): A = self._points[i] B = self._points[i+1] if np.any(great_circle_arc.intersects( A, B, other._points[:-1], other._points[1:])): return True return False
[docs] def intersects_arc(self, a, b): """ Determines if this `SingleSphericalPolygon` intersects or contains the given arc. """ P = self._points if self.contains_arc(a, b): return True intersects = great_circle_arc.intersects(P[:-1], P[1:], a, b) return np.any(intersects)
[docs] def contains_arc(self, a, b): """ Returns `True` if the polygon fully encloses the arc given by a and b. """ return self.contains_point(a) and self.contains_point(b)
[docs] def area(self): r""" Returns the area of the polygon on the unit sphere, in steradians. The area is computed using a generalization of Girard's Theorem. if :math:`\theta` is the sum of the internal angles of the polygon, and *n* is the number of vertices, the area is: .. math:: S = \theta - (n - 2) \pi The area can be negative if the points on the polygon are ordered counter-clockwise. Take the absolute value if that is not desired. """ if len(self._points) < 3: return np.array(0.0) points = np.vstack((self._points, self._points[1])) angles = great_circle_arc.angle(points[:-2], points[1:-1], points[2:]) return np.sum(angles) - (len(angles) - 2) * np.pi
[docs] def union(self, other): """ Return a new `SphericalPolygon` that is the union of *self* and *other*. Parameters ---------- other : `SingleSphericalPolygon` Returns ------- polygon : `SphericalPolygon` object See also -------- SphericalPolygon.multi_union Notes ----- For implementation details, see the :mod:`~spherical_geometry.graph` module. """ from . import graph if len(self._points) < 3: return SphericalPolygon([other.copy()]) elif len(other._points) < 3: return SphericalPolygon([self.copy()]) g = graph.Graph([self, other]) return g.union()
def _find_new_inside(self): """ Finds an acceptable inside point inside of *points* that is also inside of *polygons*. """ npoints = len(self._points) if npoints > 4: points = np.vstack((self._points, self._points[1])) A = points[:-2] B = points[1:-1] C = points[2:] orient = great_circle_arc.triple_product(A-B, C-B, B) if np.sum(orient) < 0.0: orient = -1.0 * orient midpoint = great_circle_arc.midpoint(A, C) candidate = max(zip(orient, midpoint), key=lambda x: x[0]) inside = candidate[1] else: # Fall back on computing the mean point inside = self._points.mean(axis=0) vector.normalize_vector(inside, output=inside) return inside def _find_new_outside(self): """ Finds an acceptable point outside of the polygon """ tagged_points = [] points = self._points[:-1] # Compute the minimum distance between all polygon points # and each antipode to a polygon point for point in points: point = -1.0 * point dot = great_circle_arc.inner1d(point, points) tag = np.amax(dot) tagged_points.append((tag, point)) # find the antipode with the maximum distance # to any polygon point. It is our outside point. (tag, point) = min(tagged_points, key=lambda p: p[0]) return point
[docs] def intersection(self, other): """ Return a new `SphericalPolygon` that is the intersection of *self* and *other*. If the intersection is empty, a `SphericalPolygon` with zero subpolyons will be returned. Parameters ---------- other : `SingleSphericalPolygon` Returns ------- polygon : `SphericalPolygon` object See also -------- SphericalPolygon.multi_union Notes ----- For implementation details, see the :mod:`~spherical_geometry.graph` module. """ from . import graph if len(self._points) < 3 or len(other._points) < 3: return SphericalPolygon([]) g = graph.Graph([self, other]) return g.intersection()
[docs] def overlap(self, other): r""" Returns the fraction of *self* that is overlapped by *other*. Let *self* be *a* and *other* be *b*, then the overlap is defined as: .. math:: \frac{S_{a \cap b}}{S_a} Parameters ---------- other : `SingleSphericalPolygon` Returns ------- frac : float The fraction of *self* that is overlapped by *other*. """ s1 = self.area() intersection = self.intersection(other) s2 = intersection.area() return abs(s2 / s1)
[docs] def draw(self, m, **plot_args): """ Draws the polygon in a matplotlib.Basemap axes. Parameters ---------- m : Basemap axes object **plot_args : Any plot arguments to pass to basemap """ if not len(self._points): return if not len(plot_args): plot_args = {'color': 'blue'} points = self._points if 'alpha' in plot_args: del plot_args['alpha'] alpha = 1.0 for A, B in zip(points[0:-1], points[1:]): length = np.rad2deg(great_circle_arc.length(A, B)) if not np.isfinite(length): length = 2 interpolated = great_circle_arc.interpolate(A, B, length * 4) lon, lat = vector.vector_to_lonlat( interpolated[:, 0], interpolated[:, 1], interpolated[:, 2], degrees=True) for lon0, lat0, lon1, lat1 in zip(lon[0:-1], lat[0:-1], lon[1:], lat[1:]): m.drawgreatcircle(lon0, lat0, lon1, lat1, alpha=alpha, **plot_args) alpha -= 1.0 / len(points) lon, lat = vector.vector_to_lonlat( *self._inside, degrees=True) x, y = m(lon, lat) m.scatter(x, y, 1, **plot_args)
# For backwards compatibility _SingleSphericalPolygon = SingleSphericalPolygon
[docs] class SphericalPolygon(SingleSphericalPolygon): r""" Polygons are represented by both a set of points (in Cartesian (*x*, *y*, *z*) normalized on the unit sphere), and an inside point. The inside point is necessary, because both the inside and outside of the polygon are finite areas on the great sphere, and therefore we need a way of specifying which is which. This class contains a list of disjoint closed polygons. """ def __init__(self, init, inside=None): r""" Parameters ---------- init : object May be either: - A list of disjoint `SphericalPolygon` objects. - An Nx3 array of (*x*, *y*, *z*) triples in Cartesian space. These points define the boundary of the polygon. It may contain zero points, in which it defines the null polygon. It may not contain one or two points. inside : An (*x*, *y*, *z*) triple, optional If *init* is an array of points, this point must be inside the polygon. If it is not provided, one will be created. """ from . import graph for polygon in init: if not isinstance(polygon, (SphericalPolygon, SingleSphericalPolygon)): break else: self._polygons = tuple(init) return self._polygons = (SingleSphericalPolygon(init, inside),) polygons = [] for polygon in self: g = graph.Graph((polygon,)) polygons.extend(g.disjoint_polygons()) self._polygons = polygons def __copy__(self): return deepcopy(self) copy = __copy__ def __len__(self): return len(self._polygons) def __repr__(self): buffer = [] for polygon in self._polygons: buffer.append(repr(polygon)) return '[' + ',\n'.join(buffer) + ']' def __iter__(self): """ Iterate over all base polygons that make up this multi-polygon set. """ for polygon in self._polygons: for subpolygon in polygon: yield subpolygon # Alias for backwards compatibility iter_polygons_flat = __iter__ @property def points(self): """ The points defining the polygons. It is an iterator over disjoint closed polygons, where each element is an Nx3 array of (*x*, *y*, *z*) vectors. Each polygon is explicitly closed, i.e., the first and last points are the same. """ for polygon in self: yield polygon.points @property def inside(self): """ Iterate over the inside point of each of the polygons. """ for polygon in self: yield polygon.inside @property def polygons(self): """ Get a sequence of all of the subpolygons. Each subpolygon may itself have subpolygons. To get a flattened sequence of all base polygons, use `iter_polygons_flat`. """ return self._polygons
[docs] def is_clockwise(self): """ Return True if all subpolygons are clockwise """ all = True any = False for polygon in self._polygons: cw = polygon.is_clockwise() all = all and cw any = any or cw if all and any: cw = True elif not all and not any: cw = False else: cw = None return cw
[docs] @staticmethod def self_intersect(points): """ Return true if the path defined by a list of points intersects itself """ from . import graph polygon = SingleSphericalPolygon(points) g = graph.Graph((polygon,)) return g._find_all_intersections()
[docs] def to_lonlat(self): """ Convert the `SphericalPolygon` footprint to longitude and latitude coordinates. Returns ------- polyons : iterator Each element in the iterator is a tuple of the form (*lon*, *lat*), where each is an array of points. """ for polygon in self: yield polygon.to_lonlat()
# to_ra_dec is an alias for to_lonlat to_radec = to_lonlat
[docs] @classmethod def from_lonlat(cls, lon, lat, center=None, degrees=True): # TODO Move into SingleSphericalPolygon r""" Create a new `SphericalPolygon` from a list of (*longitude*, *latitude*) points. Parameters ---------- lon, lat : 1-D arrays of the same length The vertices of the polygon in longitude and latitude. center : (*lon*, *lat*) pair, optional A point inside of the polygon to define its inside. degrees : bool, optional If `True`, (default) *lon* and *lat* are in decimal degrees, otherwise in radians. Returns ------- polygon : `SphericalPolygon` object """ polygon = SingleSphericalPolygon.from_lonlat(lon, lat, center, degrees) return cls((polygon,))
# from_radec is an alias for from_lon_lat from_radec = from_lonlat
[docs] @classmethod def from_cone(cls, lon, lat, radius, degrees=True, steps=16): r""" Create a new `SphericalPolygon` from a cone (otherwise known as a "small circle") defined using (*lon*, *lat*, *radius*). The cone is not represented as an ideal circle on the sphere, but as a series of great circle arcs. The resolution of this conversion can be controlled using the *steps* parameter. Parameters ---------- lon, lat : float scalars This defines the center of the cone radius : float scalar The radius of the cone degrees : bool, optional If `True`, (default) *lon*, *lat* and *radius* are in decimal degrees, otherwise in radians. steps : int, optional The number of steps to use when converting the small circle to a polygon. Returns ------- polygon : `SphericalPolygon` object """ polygon = SingleSphericalPolygon.from_cone(lon, lat, radius, degrees=degrees, steps=steps) return cls((polygon,))
[docs] @classmethod def from_wcs(cls, fitspath, steps=1, crval=None): r""" Create a new `SphericalPolygon` from the footprint of a FITS WCS specification. This method requires having `astropy <http://astropy.org>`__ installed. Parameters ---------- fitspath : path to a FITS file, `astropy.io.fits.Header`, or `astropy.wcs.WCS` Refers to a FITS header containing a WCS specification. steps : int, optional The number of steps along each edge to convert into polygon edges. Returns ------- polygon : `SphericalPolygon` object """ polygon = SingleSphericalPolygon.from_wcs(fitspath, steps=steps, crval=crval) return cls((polygon,))
[docs] @classmethod def convex_hull(cls, points): r""" Create a new `SphericalPolygon` from the convex hull of a list of points. Parameters ---------- points: A list of points on the unit sphere Returns ------- polygon : `SphericalPolygon` object """ polygon = SingleSphericalPolygon.convex_hull(points) return cls((polygon,))
[docs] def invert_polygon(self): """ Construct a polygon which is the inverse (complement) of the original polygon """ if len(self._polygons) != 1: raise RuntimeError("Can only invert a single polygon") klass = self.__class__ inverted_polygon = self._polygons[0].invert_polygon() return klass((inverted_polygon, ))
[docs] def contains_point(self, point): r""" Determines if this `SphericalPolygon` contains a given point. Parameters ---------- point : an (*x*, *y*, *z*) triple The point to test. Returns ------- contains : bool Returns `True` if the polygon contains the given *point*. """ for polygon in self: if polygon.contains_point(point): return True return False
[docs] def contains_lonlat(self, lon, lat, degrees=True): r""" Determines if this `SphericalPolygon` contains a given longitude and latitude. Parameters ---------- lon, lat: Longitude and latitude. Must be scalars. degrees : bool, optional If `True`, (default) *lon* and *lat* are in decimal degrees, otherwise in radians. Returns ------- contains : bool Returns `True` if the polygon contains the given *point*. """ for polygon in self: if polygon.contains_lonlat(lon, lat, degrees=degrees): return True return False
# Alias for contains_lonlat contains_radec = contains_lonlat
[docs] def intersects_poly(self, other): r""" Determines if this `SphericalPolygon` intersects another `SphericalPolygon`. This method is much faster than actually computing the intersection region between two polygons. Parameters ---------- other : `SphericalPolygon` Returns ------- intersects : bool Returns `True` if this polygon intersects the *other* polygon. """ if not isinstance(other, SphericalPolygon): raise TypeError for polya in self: for polyb in other: if polya.intersects_poly(polyb): return True return False
[docs] def intersects_arc(self, a, b): """ Determines if this `SphericalPolygon` intersects or contains the given arc. """ for subpolygon in self: if subpolygon.intersects_arc(a, b): return True return False
[docs] def contains_arc(self, a, b): """ Returns `True` if the polygon fully encloses the arc given by a and b. """ for subpolygon in self: if subpolygon.contains_arc(a, b): return True return False
[docs] def area(self): r""" Returns the area of the polygon on the unit sphere in steradians. The area is computed using a generalization of Girard's Theorem. if :math:`\theta` is the sum of the internal angles of the polygon, and *n* is the number of vertices, the area is: .. math:: S = \theta - (n - 2) \pi """ area = 0.0 for subpoly in self: area += subpoly.area() return area
[docs] def union(self, other): """ Return a new `SphericalPolygon` that is the union of *self* and *other*. Parameters ---------- other : `SphericalPolygon` Returns ------- polygon : `SphericalPolygon` object See also -------- multi_union Notes ----- For implementation details, see the :mod:`~spherical_geometry.graph` module. """ from . import graph if self.area() == 0.0: return other.copy() elif other.area() == 0.0: return self.copy() g = graph.Graph(list(self.iter_polygons_flat()) + list(other.iter_polygons_flat())) return g.union()
[docs] @classmethod def multi_union(cls, polygons): """ Return a new `SphericalPolygon` that is the union of all of the polygons in *polygons*. Currently this implementation exhibits exponential time behavior and becomes practically unusable when dealing with on the order of 40 or more polygons. Also, current implementation struggles when some of the input polygons are nearly identical. As a workaround, this method pre-filters input polygons and excludes those nearly the same as some other input polygon. Two poligons treated as the same polygon if their vertices (``x``, ``y``, and ``z`` cordinates on a unit sphere) differ by less than ``5e-9``. This is equivalent to polygon vertices being separated by less than 0.0015 arcsec on the sky or by less than ``2 mm`` on Earth (at average Earth radius). Parameters ---------- polygons : sequence of `SphericalPolygon` Returns ------- polygon : `SphericalPolygon` object See also -------- union """ if not len(polygons): raise ValueError for polygon in polygons: if not isinstance(polygon, SphericalPolygon): raise TypeError("Expected a sequence of SphericalPolygon") # Next block is a workaround to a bug in the graph code that leads to a # crash when computing multi_union of polygons # when some of input polygons are very close to each other. # Remove the next block once the bug is fixed. # See https://github.com/spacetelescope/spherical_geometry/issues/232 # # This woraround will result in two poligons treated as the same # polygon if their vertices (x, y, z on a unit sphere) differ by 5e-9. # This is equivalent to polygon vertices being separated by less than # 0.0015 arcsec on the sky or by less than 2mm on Earth (at average # Earth radius). accepted_polygon_points = [np.sort(list(polygons[0].points)[0], axis=0)] filtered_polygons = [polygons[0]] for p in polygons[1:]: pts = np.sort(list(p.points)[0], axis=0) for pts2 in accepted_polygon_points: if (pts.size == pts2.size and np.allclose(pts, pts2, rtol=0, atol=5e-9)): break else: filtered_polygons.append(p) accepted_polygon_points.append(pts) continue from . import graph all_polygons = [] for polygon in filtered_polygons: all_polygons.extend(polygon.iter_polygons_flat()) g = graph.Graph(all_polygons) return g.union()
[docs] def intersection(self, other): """ Return a new `SphericalPolygon` that is the intersection of *self* and *other*. If the intersection is empty, a `SphericalPolygon` with zero subpolygons will be returned. Parameters ---------- other : `SphericalPolygon` Returns ------- polygon : `SphericalPolygon` object Notes ----- For implementation details, see the :mod:`~spherical_geometry.graph` module. """ if self.area() == 0.0: return SphericalPolygon([]) elif other.area() == 0.0: return SphericalPolygon([]) all_polygons = [] for polya in self: for polyb in other: if polya.intersects_poly(polyb): subpolygons = polya.intersection(polyb) all_polygons.extend(subpolygons.iter_polygons_flat()) return SphericalPolygon(all_polygons)
[docs] @classmethod def multi_intersection(cls, polygons): """ Return a new `SphericalPolygon` that is the intersection of all of the polygons in *polygons*. Parameters ---------- polygons : sequence of `SphericalPolygon` Returns ------- polygon : `SphericalPolygon` object """ if not len(polygons): raise ValueError for polygon in polygons: if not isinstance(polygon, SphericalPolygon): raise TypeError results = None for polygon in polygons: if results is None: results = polygon elif len(results.polygons) == 0: return results else: results = results.intersection(polygon) return results
[docs] def draw(self, m, **plot_args): """ Draws the polygon in a matplotlib.Basemap axes. Parameters ---------- m : Basemap axes object **plot_args : Any plot arguments to pass to basemap """ for polygon in self._polygons: polygon.draw(m, **plot_args)